Influence of averaging method on muscle deoxygenation interpretation during repeated‐sprint exercise

Abstract

Near-infrared spectroscopy (NIRS) is a common tool used to study oxygen availability and utilization during repeated-sprint exercise. However, there are inconsistent methods of smoothing and determining peaks and nadirs from the NIRS signal, which make interpretation and comparisons between studies difficult. To examine the effects of averaging method on deoxyhaemoglobin concentration ([HHb]) trends, nine males performed ten 10-s sprints, with 30 seconds of recovery, and six analysis methods were used for determining peaks and nadirs in the [HHb] signal. First, means were calculated over predetermined windows in the last 5 and 2 seconds of each sprint and recovery period. Second, moving 5-seconds and 2-seconds averages were also applied, and peaks/nadirs were determined for each 40-seconds sprint/recovery cycle. Third, a Butterworth filter was used to smooth the signal, and the resulting signal output was used to determine peaks and nadirs from predetermined time points and a rolling approach. Correlation and residual analysis showed that the Butterworth filter attenuated the "noise" in the signal, while maintaining the integrity of the raw data (r = .9892; mean standardized residual -9.71 × 10 ± 3.80). Means derived from predetermined windows, irrespective of length and data smoothing, underestimated the magnitude of peak and nadir [HHb] compared to a rolling mean approach. Consequently, sprint-induced metabolic changes (inferred from Δ[HHb]) were underestimated. Based on these results, we suggest using a digital filter to smooth NIRS data, rather than an arithmetic mean, and a rolling approach to determine peaks and nadirs for accurate interpretation of muscle oxygenation trends.

Vascular and oxygenation responses of local ischemia and systemic hypoxia during arm cycling repeated sprints

“…NIRS measurements and analysis of peripheral oxygenation of the biceps brachii (PortaMonArtinis, Zetten, The Netherlands) were performed similarly as in Willis et al 2 Signals were recorded at 10 Hz and exported (Oxysoft 3.0.53, Artinis, The Netherlands), and application of a 4 th -order low-pass zero-phase Butterworth filter (cutoff frequency of 0.2 Hz) was used to reduce artifacts and smooth perturbations in the signal from pedaling strokes. 15 For each sprint, the maximum and minimum were detected automatically using the rapidly changing increase in deoxyhemoglobin as the visual parameter to confirm the starting point of the test. Identification of successive sprint and recovery phases was made and sprint phases were further analyzed.…”

Muscle oxygenation maintained during repeated sprints despite inspiratory muscle loading

“…After a 7-min warm-up consisting of 5 min of unloaded cycling at 60-70 rpm and two 4 s sprints (separated by 1 min), subjects rested for another 2.5 min before the repeated-sprint protocol was initiated. The repeated-sprint protocol was ten consecutive 10 s sprints separated by 30 s passive rest (4, 21–23). Subjects were instructed to give an “all-out” effort for every sprint and verbally encouraged throughout to promote a maximal effort.…”

“…Tourniquet pressure was monitored continuously to ensure it remained at 350 mm Hg for the duration of the occlusion period. To obtain one value per sprint and recovery for vastus lateralis, peaks and nadirs were identified for each period using a rolling approach (HHb VL ) (21). Time to peak HHb VL (TTP HHb ) was also calculated as the time from sprint onset to peak HHb.…”

Cerebral and Muscle Oxygenation during Repeated Shuttle Run Sprints with Hypoventilation

“…A sliding window averaging data over a 4-sec period was thus used for all NIRS variables. It has recently been demonstrated that the use of a digital filter to smooth NIRS data combined with a rolling approach was the best method to determine peaks and nadirs for accurate interpretation of muscle oxygenation trends during repeated sprint exercise [27].…”